A Circular Statistical Method for Extracting Rotation Measures

Abstract

We propose a new method for the extraction of Rotation Measure from spectral polarization data. The method is based on maximum likelihood analysis and takes into account the circular nature of the polarization data. The method is unbiased and statistically more efficient than the standard ${\chi }^2$ procedure. We also find that the method is computationally much faster than the standard ${\chi }^2$ procedure if the number of data points are very large.

17 pages, 5 figures

References in corpus (2)

• Covariant Symmetry Classifications for Observables of Cosmological Birefringence
• Relativistic beaming effects in the spectra of cores and hotspots in radio galaxies and quasars

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